from django.test import TestCase

# Create your tests here.

import whisper


def audio_tran():
    model = whisper.load_model("turbo")

    # load audio and pad/trim it to fit 30 seconds
    audio_file = r'C:\Users\86182\Downloads\车陂圆塘大街.m4a'
    audio = whisper.load_audio("audio_file")
    audio = whisper.pad_or_trim(audio)

    # make log-Mel spectrogram and move to the same device as the model
    mel = whisper.log_mel_spectrogram(audio, n_mels=model.dims.n_mels).to(model.device)

    # detect the spoken language
    _, probs = model.detect_language(mel)
    print(f"Detected language: {max(probs, key=probs.get)}")

    # decode the audio
    options = whisper.DecodingOptions()
    result = whisper.decode(model, mel, options)

    # print the recognized text
    print(result.text)

if __name__ == '__main__':
    model = whisper.load_model("small")
    audio_file = r'C:\Users\86182\Downloads\车陂圆塘大街.m4a'
    result = model.transcribe(audio_file)
    print(result["text"])